data mining: opportunities and challenges
Chapter XX - Critical and Future Trends in Data Mining A Review of Key Data Mining Technologies/Applications
Data Mining: Opportunities and Challenges
by John Wang (ed) 
Idea Group Publishing 2003
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This chapter has discussed a number of technologies, approaches, and research areas that have been identified as having critical and future promise in the field of DM. For instance, with the Web becoming such as important part of the computing community, it is not surprising that Web mining is one of the most promising areas in DM. There are several areas of Web-based mining, all of which can bring about exciting new knowledge about information on the Web, Web-usage patterns, and the intricacies of how the Web has been "woven." Coupled with this is the explosion in the amount of information that we now produce and have access to-much in the form of electronic and hard-copy text documents. Mining information from these text sources can uncover important information that had previously been buried in all of our reports, correspondence, memos, and other paperwork. The extensive use of handheld, wireless, and other ubiquitous devices is another developing area, since a lot of information being created and transmitted would be maintained and stored only on these kinds of devices. Among the other areas that have been developed, investigated, and identified are hypertext and hypermedia DM, which involves the processing and analysis of varying kinds of data; phenomenal DM, which looks at identifying phenomenon associated with a set of data; the mining of visual-oriented information; and the mining of other kinds of specialized information.

Another issue to look at is the social impact of mining for knowledge from data. This includes whether DM can be considered a threat to data security and privacy. In fact, there are daily instances where data is being collected on individuals, in effect "profiling users." Consider the many transactions that one conducts on a daily basis; it would not be difficult to understand the concerns that some have about the potential dangers of misuse of information, e.g., surfing the Web, replying to an Internet newsgroup, subscribing to a magazine, renting a video, joining a club, or making a purchase/ transaction with a credit card, supermarket loyalty card, or frequent flyer card-all of these are opportunities for someone to collect personal information.

In closing, it would not be overly optimistic to say that DM has a bright and promising future, and that the years to come will bring many new developments, methods, and technologies. While some analysts and experts in the field caution that DM may go the way of artificial intelligence (AI) and end up not having the commercial success which was predicted, the field of DM is still young enough that the possibilities are still limitless. By expanding applications that can use it, integrating technologies and methods, broadening its applicability to mainstream business applications, and making programs and interfaces easier for end-users to use, it is quite possible and likely that DM will rapidly become one of the most important and key areas of research and technology.

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Data Mining(c) Opportunities and Challenges
Data Mining: Opportunities and Challenges
ISBN: 1591400511
EAN: 2147483647
Year: 2003
Pages: 194
Authors: John Wang © 2008-2017.
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